Abstract
Emotions play a significant role in human perception and decision making. Recent studies on emotion recognition are the subject of attention by researchers from different fields. By focusing in the four emotional states: happiness, anger, sadness and a neutral state which can be always found in daily life, this dissertation studies the Physiological signal based on emotion recognition technique. This paper uses a biological signal toolbox Augsburg (AuBT) analysis of physiological signals for emotion recognition. Augsburg Biosignal Toolbox (AuBT) is a toolbox for analyzing physiological signals written in Matlab. The result of experiment show that application of Augsburg biological signal toolbox gets the overall recognition rate of 87.5%, indicating that the Augsburg Biosignal Toolbox emotion recognition is feasible.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
